Eniko Papp

Personalized genomic analyses for cancer mutation discovery and interpretation

Analysis of matched tumor and normal DNA from the same patient improves accuracy of identification of actionable mutations, allowing better targeting of potential treatments. Will the real mutation please stand up? When a patient is diagnosed with cancer, a sample of the tumor is often analyzed to look for mutations that might guide the approach to targeted treatment of the disease. Jones et al. analyzed samples from more than 800 patients with 15 different cancer types and showed that this standard approach is not necessarily accurate without also analyzing a matched sample of normal DNA from the same patient. The authors found that, compared to analysis of paired samples, the standard tumor-only sequencing approach frequently identified mutations that were present in the patient’s normal tissues and were therefore not suitable for targeted therapy or, conversely, missed useful new mutations in the tumor. Massively parallel sequencing approaches are beginning to be used clinically to characterize individual patient tumors and to select therapies based on the identified mutations. A major question in these analyses is the extent to which these methods identify clinically actionable alterations and whether the examination of the tumor tissue alone is sufficient or whether matched normal DNA should also be analyzed to accurately identify tumor-specific (somatic) alterations. To address these issues, we comprehensively evaluated 815 tumor-normal paired samples from patients of 15 tumor types. We identified genomic alterations using next-generation sequencing of whole exomes or 111 targeted genes that were validated with sensitivities >95% and >99%, respectively, and specificities >99.99%. These analyses revealed an average of 140 and 4.3 somatic mutations per exome and targeted analysis, respectively. More than 75% of cases had somatic alterations in genes associated with known therapies or current clinical trials. Analyses of matched normal DNA identified germline alterations in cancer-predisposing genes in 3% of patients with apparently sporadic cancers. In contrast, a tumor-only sequencing approach could not definitively identify germline changes in cancer-predisposing genes and led to additional false-positive findings comprising 31% and 65% of alterations identified in targeted and exome analyses, respectively, including in potentially actionable genes. These data suggest that matched tumor-normal sequencing analyses are essential for precise identification and interpretation of somatic and germline alterations and have important implications for the diagnostic and therapeutic management of cancer patients.

The genomic landscape of response to EGFR blockade in colorectal cancer

Colorectal cancer is the third most common cancer worldwide, with 1.2 million patients diagnosed annually. In late-stage colorectal cancer, the most commonly used targeted therapies are the monoclonal antibodies cetuximab and panitumumab, which prevent epidermal growth factor receptor (EGFR) activation. Recent studies have identified alterations in KRAS and other genes as likely mechanisms of primary and secondary resistance to anti-EGFR antibody therapy. Despite these efforts, additional mechanisms of resistance to EGFR blockade are thought to be present in colorectal cancer and little is known about determinants of sensitivity to this therapy. To examine the effect of somatic genetic changes in colorectal cancer on response to anti-EGFR antibody therapy, here we perform complete exome sequence and copy number analyses of 129 patient-derived tumour grafts and targeted genomic analyses of 55 patient tumours, all of which were KRAS wild-type. We analysed the response of tumours to anti-EGFR antibody blockade in tumour graft models and in clinical settings and functionally linked therapeutic responses to mutational data. In addition to previously identified genes, we detected mutations in ERBB2, EGFR, FGFR1, PDGFRA, and MAP2K1 as potential mechanisms of primary resistance to this therapy. Novel alterations in the ectodomain of EGFR were identified in patients with acquired resistance to EGFR blockade. Amplifications and sequence changes in the tyrosine kinase receptor adaptor gene IRS2 were identified in tumours with increased sensitivity to anti-EGFR therapy. Therapeutic resistance to EGFR blockade could be overcome in tumour graft models through combinatorial therapies targeting actionable genes. These analyses provide a systematic approach to evaluating response to targeted therapies in human cancer, highlight new mechanisms of responsiveness to anti-EGFR therapies, and delineate new avenues for intervention in managing colorectal cancer.

Direct detection of early-stage cancers using circulating tumor DNA

Noninvasive liquid biopsy analysis of circulating tumor DNA permits direct detection of early-stage cancers. Finding smaller needles in haystacks The detection and analysis of cell-free DNA in patients’ blood are becoming increasingly accepted in oncology. However, this approach has generally been applied for the monitoring of patients with existing tumors. It has not been useful for early diagnosis of cancer because of insufficient sensitivity to detect really small tumors that only shed minute quantities of DNA into the blood, as well as difficulties with identifying cancer-associated genetic changes without knowing what mutations are present in the primary tumor. A method developed by Phallen et al., called targeted error correction sequencing, addresses both of these limitations and demonstrates the feasibility of detecting circulating cell-free DNA from many early tumors, suggesting its potential use for cancer screening. Early detection and intervention are likely to be the most effective means for reducing morbidity and mortality of human cancer. However, development of methods for noninvasive detection of early-stage tumors has remained a challenge. We have developed an approach called targeted error correction sequencing (TEC-Seq) that allows ultrasensitive direct evaluation of sequence changes in circulating cell-free DNA using massively parallel sequencing. We have used this approach to examine 58 cancer-related genes encompassing 81 kb. Analysis of plasma from 44 healthy individuals identified genomic changes related to clonal hematopoiesis in 16% of asymptomatic individuals but no alterations in driver genes related to solid cancers. Evaluation of 200 patients with colorectal, breast, lung, or ovarian cancer detected somatic mutations in the plasma of 71, 59, 59, and 68%, respectively, of patients with stage I or II disease. Analyses of mutations in the circulation revealed high concordance with alterations in the tumors of these patients. In patients with resectable colorectal cancers, higher amounts of preoperative circulating tumor DNA were associated with disease recurrence and decreased overall survival. These analyses provide a broadly applicable approach for noninvasive detection of early-stage tumors that may be useful for screening and management of patients with cancer.

High grade serous ovarian carcinomas originate in the fallopian tube

High-grade serous ovarian carcinoma (HGSOC) is the most frequent type of ovarian cancer and has a poor outcome. It has been proposed that fallopian tube cancers may be precursors of HGSOC but evolutionary evidence for this hypothesis has been limited. Here, we perform whole-exome sequence and copy number analyses of laser capture microdissected fallopian tube lesions (p53 signatures, serous tubal intraepithelial carcinomas (STICs), and fallopian tube carcinomas), ovarian cancers, and metastases from nine patients. The majority of tumor-specific alterations in ovarian cancers were present in STICs, including those affecting TP53, BRCA1, BRCA2 or PTEN. Evolutionary analyses reveal that p53 signatures and STICs are precursors of ovarian carcinoma and identify a window of 7 years between development of a STIC and initiation of ovarian carcinoma, with metastases following rapidly thereafter. Our results provide insights into the etiology of ovarian cancer and have implications for prevention, early detection and therapeutic intervention of this disease.It has previously been proposed that high-grade serous ovarian carcinoma (HGSOC) may originate from the fallopian tube. Here, the authors analyze genetic aberrances in fallopian tube lesions, ovarian cancers, and metastases from HGSOC patients and establish the evolutionary origins of HGSOC in the fallopian tube.

Beyond genomics: Critical evaluation of cell line utility for ovarian cancer research

OBJECTIVE Comparisons of The Cancer Genome Atlas (TCGA) with high grade serous ovarian cancer (HGSOC) cell lines used in research reveal that many common experimental models lack defining genomic characteristics seen in patient tumors. As cell lines exist with higher genomic fidelity to TCGA, this study aimed to evaluate the utility of these cell lines as tools for preclinical investigation. METHODS We compared two HGSOC cell lines with supposed high genomic fidelity to TCGA, KURAMOCHI and OVSAHO, with the most commonly cited ovarian cancer cell line, SKOV3, which has poor genomic fidelity to TCGA. The lines were analyzed for genomic alterations, in vitro performance, and growth in murine xenografts. RESULTS Using targeted next generation sequencing analyses, we determined that each line had a distinct mutation profile, including alterations in TP53, and copy number variation of specific genes. KURAMOCHI and OVSAHO better recapitulated serous carcinoma morphology than SKOV3. All lines expressed PAX8 and stathmin, but KURAMOCHI and OVSAHO did not express CK7. KURAMOCHI was significantly more platinum sensitive than OVSAHO and SKOV3. Unlike SKOV3, KURAMOCHI and OVSAHO engrafted poorly in subcutaneous xenografts. KURAMOCHI and OVSAHO grew best after intraperitoneal injection in SCID mice and recapitulated miliary disease while SKOV3 grew in all murine systems and formed oligometastatic disease. CONCLUSIONS The research utility of HGSOC cell line models requires a comprehensive assessment of genomic as well as in vitro and in vivo properties. Cell lines with closer genomic fidelity to human tumors may have limitations in performance for preclinical investigation.

Establishment of patient-derived tumor xenograft models of epithelial ovarian cancer for preclinical evaluation of novel therapeutics

Purpose: Ovarian cancer is the leading cause of death from gynecologic malignancy in the United States, with high rates of recurrence and eventual resistance to cytotoxic chemotherapy. Model systems that allow for accurate and reproducible target discovery and validation are needed to support further drug development in this disease. Experimental Design: Clinically annotated patient-derived xenograft (PDX) models were generated from tumor cells isolated from the ascites or pleural fluid of patients undergoing clinical procedures. Models were characterized by IHC and by molecular analyses. Each PDX was luciferized to allow for reproducible in vivo assessment of intraperitoneal tumor burden by bioluminescence imaging (BLI). Plasma assays for CA125 and human LINE-1 were developed as secondary tests of in vivo disease burden. Results: Fourteen clinically annotated and molecularly characterized luciferized ovarian PDX models were generated. Luciferized PDX models retain fidelity to both the nonluciferized PDX and the original patient tumor, as demonstrated by IHC, array CGH, and targeted and whole-exome sequencing analyses. Models demonstrated diversity in specific genetic alterations and activation of PI3K signaling pathway members. Response of luciferized PDX models to standard-of-care therapy could be reproducibly monitored by BLI or plasma markers. Conclusions: We describe the establishment of a collection of 14 clinically annotated and molecularly characterized luciferized ovarian PDX models in which orthotopic tumor burden in the intraperitoneal space can be followed by standard and reproducible methods. This collection is well suited as a platform for proof-of-concept efficacy and biomarker studies and for validation of novel therapeutic strategies in ovarian cancer. Clin Cancer Res; 23(5); 1263–73. ©2016 AACR.

A machine learning approach for somatic mutation discovery

A machine learning approach to detect somatic mutations in cancer patients outperforms existing methods and may improve clinical outcome. Calling it like the algorithm sees it Somatic mutation calling is essential for the proper diagnosis and treatment of most cancer patients. Wood et al. developed a machine learning approach called Cerebro that increased the accuracy of calling validated somatic mutations in tumor samples from cancer patients. Cerebro outperformed six other mutation detection methods by better distinguishing technical sequencing artifacts. An analysis of non–small cell lung cancer and melanoma patient samples revealed that Cerebro more accurately classified patients according to their immunotherapy response, suggesting that the authors’ mutation calling approach could favorably affect patient care. Variability in the accuracy of somatic mutation detection may affect the discovery of alterations and the therapeutic management of cancer patients. To address this issue, we developed a somatic mutation discovery approach based on machine learning that outperformed existing methods in identifying experimentally validated tumor alterations (sensitivity of 97% versus 90 to 99%; positive predictive value of 98% versus 34 to 92%). Analysis of paired tumor-normal exome data from 1368 TCGA (The Cancer Genome Atlas) samples using this method revealed concordance for 74% of mutation calls but also identified likely false-positive and false-negative changes in TCGA data, including in clinically actionable genes. Determination of high-quality somatic mutation calls improved tumor mutation load–based predictions of clinical outcome for melanoma and lung cancer patients previously treated with immune checkpoint inhibitors. Integration of high-quality machine learning mutation detection in clinical next-generation sequencing (NGS) analyses increased the accuracy of test results compared to other clinical sequencing analyses. These analyses provide an approach for improved identification of tumor-specific mutations and have important implications for research and clinical management of cancer patients.

Abstract 3894: The importance of matched tumor and normal DNA for somatic mutation discovery and clinical interpretation

Proceedings: AACR 106th Annual Meeting 2015; April 18-22, 2015; Philadelphia, PA Massively parallel sequencing approaches are beginning to be used clinically to characterize individual patient tumors and to identify targeted therapies based on mutations identified. A major question in these analyses is the extent to which these methods identify clinically actionable alterations in patients and whether the examination of the tumor tissue alone is sufficient or whether matched normal DNA should also be analyzed to accurately identify tumor-specific (somatic) alterations. To address these issues, we comprehensively evaluated tumor-normal paired samples from 753 cancers from fourteen tumor types. We analyzed somatic alterations using whole exome or targeted next generation sequencing approaches that were validated with high sensitivity and specificity. These analyses revealed an average of 140 and 4.34 somatic changes per exome and targeted analyses, respectively. Approximately 65% of cases had somatic alterations in genes associated with known therapies or current clinical trials. In contrast, a tumor-only sequencing approach followed by bioinformatic removal of common germline variants from existing databases led to a 36% and 58% false discovery rate in alterations identified in targeted and exome analyses, respectively, including in potentially actionable genes. These data suggest that matched tumor-normal sequencing analyses are essential for precise identification and interpretation of somatic alterations and have important implications for the diagnostic and therapeutic management of cancer patients. Citation Format: Siân Jones, Mark Sausen, Valsamo Anagnostou, Samuel V. Angiuoli, Bryan Chesnick, Kevin Galens, Maura Kadan, Lisa Kann, Karli Lytle, Derek Murphy, Monica Nesselbush, Eniko Papp, Sonya Parpart-Li, David Riley, Manish Shukla, Theresa Zhang, Luis A. Diaz, Victor E. Velculescu. The importance of matched tumor and normal DNA for somatic mutation discovery and clinical interpretation. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3894. doi:10.1158/1538-7445.AM2015-3894

Abstract 867: Therapeutic potential of small molecule SYK inhibitors for treatment of primary B cell acute lymphoblastic leukemia

Proceedings: AACR 103rd Annual Meeting 2012‐‐ Mar 31‐Apr 4, 2012; Chicago, IL Background: B-cell acute lymphoblastic leukemia (B-ALL) is the most common childhood cancer. Intensified and central nervous system (CNS)-directed chemotherapy has significantly improved outcomes for pediatric patients but are associated with late-effect morbidities. Moreover, ∼20% pediatric and a higher frequency of adult patients suffer relapses that are often fatal. Thus there is a need to develop therapies that target signaling abnormalities in B-ALL, which may reduce complications of CNS leukemia and decrease long-term morbidities. Rationale: Using a p53-/- SCID mouse model of B-ALL we observed pre-B cell receptor (pre-BCR)-independent activation of the spleen tyrosine kinase (SYK) and found that it was crucial for the proliferation and survival of these leukemias. We then asked whether abnormal SYK activation occurs in human B-ALL and whether these cells are sensitive to small molecule SYK inhibitors. Methods: Viably frozen diagnostic B-ALL samples from children (n=54) and adults (n=42) tested for sensitivity to SYK inhibitors R406 (Astra-Zeneca) and BAY61-3606 in a short-term in vitro proliferation assay. Phospho-flow cytometry was also performed to quantify phosphorylation of SYK and other signaling proteins in B-ALL samples. The R406 pro-drug (Fostamatinib: Fosta) was used in a xenotransplant assay to determine therapeutic potential of SYK inhibition in vivo. Results: Phospho-flow cytometry profiling of primary B-ALL samples revealed prominent phosphorylation of SYK (Y348) and downstream signaling proteins that was decreased by SYK inhibitors. Furthermore, SYK inhibitors significantly attenuated proliferation of pre-BCR-negative and pre-BCR-positive B-ALL samples indicating that SYK was required for their survival and proliferation. In contrast, FLT3 or SRC inhibitors did not inhibit proliferation of pediatric and adult B-ALL samples. Importantly, siRNA-mediated SYK knockdown also reduced proliferation of B-ALL cell lines. Therefore, we tested the therapeutic potential of SYK inhibition using xenotransplantion. NOD.SCID.gamma C-/- (NSG) mice were injected intrafemorally with primary B-ALL samples (n=9) and fed chow containing either vehicle (AIN-76A diet) or Fosta (AIN-76A diet with 2g Fosta/kg). Leukemia burden was assessed 4-8 weeks post-transplantation. Mice given the Fosta diet had significantly reduced numbers of leukemic blasts in their injected femurs, other bones, spleens and CNS as compared to vehicle-treated mice. In addition, Fosta treatment reduced spleen, liver and kidney weight in ALL-transplanted mice. Conclusion: SYK signaling is vital to B cell acute lymphoblastic leukemia survival; small molecule SYK inhibitors have therapeutic potential in poor-prognosis and relapsed B-ALL. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 867. doi:1538-7445.AM2012-867